System and method for creating, storing, and utilizing composite images of a geographic location

ABSTRACT

A system and method synthesizing images of a locale to generate a composite image that provide a panoramic view of the locale. A video camera moves along a street recording images of objects along the street. A GPS receiver and inertial navigation system provide the position of the camera as the images are being recorded. The images are indexed with the position data provided by the GPS receiver and inertial navigation system. The composite image is created on a column-by-column basis by determining which of the acquired images contains the desired pixel column, extracting the pixels associated with the column, and stacking the columns side by side. The composite images are stored in an image database and associated with a street name and number range of the street being depicted in the image. The image database covers a substantial amount of a geographic area allowing a user to visually navigate the area from a user terminal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. provisional applicationentitled SYTEM FOR CREATING AND USING A VISUAL RECORD OF A GEOGRAPHICLOCATION COUPLED WITH POSITION INFORMATION, Provisional Application No.60/238,490, filed on Oct. 6, 2000 the content of which is incorporatedherein by reference.

FIELD OF THE INVENTION

This invention relates to visual databases, specifically to the creationand utilization of visual databases of geographic locations.

BACKGROUND OF THE INVENTION

There exist methods in the prior art for creating visual databases ofgeographic locations. However, such databases are of limited use due tothe method of acquiring the imagery as well as the kind of imageryacquired. One particular method involves the taking of individualphotographs of the location and electronically pasting the photographson a polygonal mesh that provide the framework for a three-dimensional(3D) rendering of the location. This method, however, is time consumingand inefficient for creating large, comprehensive databases covering asubstantial geographic area such as an entire city, state, or country.

Another method uses video technology to acquire the images. The use ofvideo technology, especially digital video technology, allows theacquisition of the image data at a higher rate, reducing the costinvolved in creating the image databases. For example, the prior artteaches the use of a vehicle equipped with a video camera and a GlobalPositioning System (GPS) to collect image and position data by drivingthrough the location. The video images are later correlated to the GPSdata for indexing the imagery. Nevertheless, such a system is stilllimited in its usefulness due to the lack of additional information onthe imagery being depicted.

The nature of the acquired imagery also limits the usefulness of such asystem. A single image acquired by the video camera contains a narrowfield of view of a locale (e.g. a picture of a single store-front) dueto the limited viewing angle of the video camera. This narrow field ofview provides little context for the object/scene being viewed. Thus, auser of such an image database may find it difficult to orient himselfor herself in the image, get familiar with the locale, and navigatethrough the database itself.

One way to increase the field of view is to use a shorter focal lengthfor the video camera, but this introduces distortions in the acquiredimage. Another method is to increase the distance between the camera andthe buildings being filmed. However, this may not be possible due to thelimit on the width of the road and constructions on the opposite side ofthe street.

The prior art further teaches the dense sampling of images of anobject/scene to provide different views of the object/scene. Thesampling is generally done in two dimensions either within a plane, oron the surface of an imaginary sphere surrounding the object/scene. Sucha sampling, however, is computationally intensive and hence cumbersomeand inefficient in terms of time and cost.

Accordingly, there is a need for a system and method for creating avisual database of a comprehensive geographic area in a more time andcost efficient manner. Such a system should not require thereconstruction of 3D scene geometry nor the dense sampling of the localein multiple dimensions. Furthermore, the images in the database shouldprovide a wider field of view of a locale to provide context to theobjects being depicted. The database should further correlate the imageswith additional information related to the geographic location andobjects in the location to further enhance the viewing experience.

SUMMARY OF THE INVENTION

The present invention addresses and alleviates the above-mentioneddeficiencies associated with the prior art. More particularly, thepresent invention is directed to a computer-implemented system andmethod for synthesizing images of a geographic location to generatecomposite images of the location. The geographic location may be aparticular street in a geographic area with the composite imagesproviding a view of the objects on each side of the street.

According to one aspect of the invention, an image recording devicemoves along a path recording images of objects along the path. A GPSreceiver and/or inertial navigation system provides position informationof the image recording device as the images are being acquired. Theimage and position information is provided to a computer to associateeach image with the position information.

The computer synthesizes image data from the acquired images to create acomposite image depicting a view of the objects from a particularlocation outside of the path. Preferably, the composite image provides afield of view of the location that is wider than the field of viewprovided by any single image acquired by the image recording device.

In another aspect of the invention, the path of the camera ispartitioned into discrete segments. Each segment is preferablyassociated with multiple composite images where each composite imagedepicts a portion of the segment. The composite images and associationinformation are then stored in an image database.

In yet another aspect of the invention, the image database containssubstantially all of the static objects in the geographic area allowinga user to visually navigate the area from a user terminal. The systemand method according to this aspect of the invention identifies acurrent location in the geographic area, retrieves an imagecorresponding to the current location, monitors a change of the currentlocation in the geographic area, and retrieves an image corresponding tothe changed location. A map of the location may also be displayed to theuser along with information about the objects depicted in the image.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic block diagram of a data acquisition and processingsystem for acquiring image and position data used to create compositeimages of a geographic location;

FIG. 2 is an illustration of a composite image created by the dataacquisition and processing system of FIG. 1;

FIG. 3 is a high-level flow diagram of the steps exercised by the dataacquisition and processing system of FIG. 1 in creating and storing thecomposite images;

FIG. 4 is a flow diagram for synchronizing image sequences with positionsequences of a recording camera according to one embodiment of theinvention;

FIG. 5 is a flow diagram of an alternative embodiment for synchronizingimage sequences with position sequences of a recording camera;

FIG. 6 is a block diagram of the data acquisition and processing systemof FIG. 1 allowing a real-time synchronization of image and positiondata;

FIG. 7 is another embodiment for synchronizing image sequences withposition sequences of a recording camera;

FIG. 8 is a flow diagram for segmenting and labeling a cameratrajectory;

FIG. 9 is an illustration of a trajectory in a single camera scenario;

FIG. 10 is a flow diagram for creating a composite image of a segment ofa camera's path;

FIG. 11 is a flow diagram for identifying and retrieving an opticalcolumn from an acquired image according to one embodiment of theinvention;

FIG. 12 is a flow diagram for identifying and retrieving an opticalcolumn from an acquired image according to an alternative embodiment ofthe invention;

FIG. 13 is an illustration of an exemplary street segments tableincluding street segments in a camera's trajectory;

FIG. 14 is an illustration of an exemplary image coordinates table forassociating composite images with the street segments in the streetsegments table of FIG. 13;

FIG. 15 is an illustration of an exemplary segment block table forallowing an efficient determination of a segment that is closest to aparticular geographic coordinate;

FIG. 16 is an illustration of an exemplary graphical user interface forallowing the user to place requests and receive information aboutparticular geographic locations;

FIG. 17 is a flow diagram of a process for obtaining image and locationinformation of an express street address; and

FIG. 18 is a flow diagram of the process for obtaining image andlocation information of a location selected from a map.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of a data acquisition and processingsystem for acquiring and processing image and position data used tocreate composite images of a geographic location. The composite imagesare created by synthesizing individual image frames acquired by a videocamera moving through the location and filming the objects in its view.The composite images may depict on urban scene including the streets andstructures of an entire city, state, or country. The composite imagesmay also depict other locales such as a zoo, national park, or theinside of a museum, allowing a user to visually navigate the locale.

The data acquisition and processing system includes one or more imagerecording devices preferably taking the form of digital video cameras 10moving along a trajectory/path and recording images on the trajectory ondigital videotapes 12. Other types of acquisition devices may also beused in combination to, or in lieu of, the digital cameras 10, such asanalog cameras. Furthermore, the video images may be recorded onoptical, magnetic, or silicon video tapes, or on any other known typesof storage devices that allow random access of particular image framesand particular video pixels within the image frames.

The data acquisition and processing system further includes a GPSreceiver 16 for receiving position information from a set of GPSsatellites 18 as the cameras 10 move along the trajectory. An inertialnavigation system 20 including one or more accelerometers and/orgyroscopes also provides position information to the data acquisitionand processing system. When the inertial navigation system 20 is used inconjunction with the GPS receiver 16, a more accurate calculation of theposition information may be produced.

In an alternative embodiment, position information is acquired usingdevices other than the inertial navigation system 20 and/or the GPSreceiver 16, such as via computer-vision-based algorithms that computepositions using video information from the video cameras 10.

The video cameras 10 provide to a multiplexer 22 a frame number and timeinformation for each image acquired via a communication link 24preferably taking the form of a LANC™ port. The GPS receiver 16 andinertial navigation system 20 also provide position information to themultiplexer 22 via communication links 26 a, 26 b, preferably taking theform of RS-232 ports. The multiplexer 22 in turn transmits the receivedframe number, time information, and position data to a data acquisitioncomputer 34 via a communication link 30, which also preferably takes theform of an RS-232 port. The computer 34 stores in a trajectory database36 the position data from the GPS receiver 16 and/or inertial navigationsystem 20 along with the frame number and time information from thevideo cameras 10. This information is then used by a post-processingsystem 38 to create the composite images.

The post-processing system 38 preferably includes a post-processingcomputer 28 in communication with a video player 39. The computer 28preferably includes a video acquisition card for acquiring and storingthe image sequences as the video player 39 plays the videotapes 12 ofthe acquired images. The computer 28 includes a processor (not shown)programmed with instructions to take the image and position data andcreate one or more composite images for storing into an image database32. The image database 32 is preferably a relational database thatresides in a mass storage device taking the form of a hard disk drive ordrive array. The mass storage device may be part of the computer 28 or aseparate database server in communication with the computer.

In an alternative embodiment, the images are transferred directly to thedata acquisition computer 34 as the images are being recorded. In thisscenario, the computer 34 is preferably equipped with the videoacquisition card and includes sufficient storage space for storing theacquired images. In this embodiment, the data acquisition computer 34preferably contains program instructions to create the composite imagesfrom the acquired images.

In general terms, a composite image of a particular geographic locationis created by using at least one video camera 10 recording a series ofvideo images of the location while moving along a path. In the onecamera scenario, the camera 10 is moved twice on the same path but inopposite directions to film the objects on both sides of the path.Movement to the camera 10 is provided by a base, platform, or motorvehicle moving at an average speed of preferably about 20 miles/hour toensure a sufficient resolution in the resulting images. Video cameraswith higher sampler rates may allow for faster acquisition speeds.

Preferably, the data acquisition and processing system uses four cameras10 mounted on top of a moving motor vehicle. Two side cameras face eachside of the path for filming objects viewed from the each side of thevehicle. A front and back cameras allow the filming of the objectsviewed from the front and back of the vehicle. The front and backcameras may be equipped with fish-eye lens for providing a wide-angleview of the path. A person skilled in the art should recognize, however,that additional cameras may be used to film the objects from differentviewing directions. For example, a duodecahedron of cameras may be usedto record the objects from all viewing directions. Furthermore, the sidecameras need not face directly to the side of the street, but may face aslightly forward or backward direction to provide a look up or down ofthe path.

As the images acquired by the cameras 10 are recorded on the videotapes12, the frame number and time associated with the images are transferredto the data acquisition computer 34. The images recorded on thevideotapes 12 are later transferred to the post-processing computer 28for further processing. Once the images are received, the computer 28stores the image data in its memory in its original form or as acompressed file using one of various well-known compression schemes,such as MPEG.

As the camera 10 moves along the path and records the objects in itsview, the GPS receiver 16 computes latitude and longitude coordinatesusing the information received from the set of GPS satellites 18 atselected time intervals (e.g. one sample every two seconds). Thelatitude and longitude coordinates indicate the position of the camera10 during the recording of a particular image frame. The GPS satellite18 also transmits to the GPS receiver 16 a Universal Time Coordinate(UTC) time of when the coordinates were acquired. The GPS receiver 16 ispreferably located on the vehicle transporting the camera 10 or on thecamera itself. The GPS data with the position sequences and UTC timeinformation is then transferred to the computer 34 for storing in thetrajectory database 36.

In addition to the position information provided by the GPS receiver 16,the inertial navigation system 20 also provides acceleration informationto the computer 34 for independently deriving the position sequence ofthe camera 10. Specifically, the one or more accelerators and gyroscopesin the inertial navigation system 20 monitor the linear and rotationalacceleration rates of the camera 10 and transfer the acceleration datato the computer 34. The computer 34 integrates the acceleration data toobtain the position of the camera 10 as a function of time. The computer34 preferably combines the position derived from the accelerationinformation with the GPS position data to produce a more accurateevaluation of the position of the camera 10 at particular instances intime.

The post-processing computer 28 uses the image and position sequences tosynthesize the acquired images and create composite images of thelocation that was filmed. The composite images preferably provide awider field of view of the location than any single image frame acquiredby the camera 10. In essence, the composite images help provide apanoramic view of the location.

FIG. 2 is an illustration of a composite image 40 created from the imageframes 42 acquired by the camera 10 while moving along an x-axis 58direction. In creating the composite image 40, the computer assumes afictitious camera 44 located behind the actual camera 10 and identifiesoptical rays 46 originating from the fictitious camera. The location ofthe fictitious camera 44 depends on the desired field of view of thelocation being filmed. The further away the fictitious camera is placedfrom the objects along the x-axis 58, the wider its field of view of theobjects.

The computer also identifies optical rays 48 originating from the actualcamera 10. For each optical ray 46 from the fictitious camera 44, thecomputer 28 selects an acquired image frame 42 that includes acorresponding optical ray 48 originating from the actual camera 10.Image data from each selected image frame 42 is then extracted andcombined to form the composite image. Preferably, the image dataextracted from each image frame is an optical column that consists of avertical set of pixels. The composite image is preferably created on acolumn-by-column basis by extracting the corresponding optical columnfrom each image frame. Thus, to create a column P_(i) 50 in thecomposite image 40, the computer locates an image frame 42 a that wasacquired when the camera 10 was located at X_(i) 52. To locate thisimage frame 42 a, the computer uses the GPS data and/or data from theinertial navigation system 20 to identify a time T_(i) 54 at which thecamera 10 was in the location X_(i) 52. Once the image frame 42 a isidentified, the computer 28 extracts the optical column 56 with an index(P_(i)/N)*M, where N is the total number of columns in the compositeimage 40 and M is the number of columns in the image frame 42 a. Thecomposite image 40 is stored in the image database 32, preferably inJPEG format, and associated with an identifier identifying theparticular geographic location depicted in the image. Furthermore,close-ups and fish-eye views of the objects are also extracted from thevideo sequences using well-known methods, and stored in the imagedatabase 32. The unused data from the acquired images is then preferablydeleted from the computer's memory.

FIG. 3 is a high-level flow diagram of the steps exercised by the dataacquisition and processing system in creating and storing the compositeimages. In step 60, the camera 10 acquires a series of images of aparticular geographic location. At the same time, the GPS receiver 16and/or inertial navigation system 20 acquires the position of the camera10 while the images are being acquired. Because the time associated withthe position information (position time) is likely to differ from thetimes of acquisition of the video images (video time), the computer 28,in step 62, synchronizes the image sequence with the position sequence.The synchronization is preferably a post-processing step that occursafter the image and position sequences have been acquired.

In step 64, the computer 28 segments the trajectory taken by therecording camera 10 into multiple segments and labels each segment withidentifying information about the segment. For example, if the cameratraverses through various streets, the computer 28 segments thetrajectory into multiple straight street segments and associates eachstreet segment with a street name and number range. In step 66, thecomputer 28 generates a series of composite images depicting a portionof each segment, and in step 68, stores each composite image in theimage database 32 along with the identifying information of the segmentwith which it is associated.

FIG. 4 is a more detailed flow diagram of step 62 for synchronizing theimage sequences with the position sequences of the recording cameraaccording to one embodiment of the invention. Although the processillustrated in FIG. 4 assumes that the position data is GPS data, aperson skilled in the art should recognize that a similar process may beemployed to synchronize the images to positions calculated using theinertial navigation system 20.

The process starts, and in step 70, a user of the system selects alandmark in the image sequence that appears in at least two distinctvideo frames. This indicates that the landmark was recorded once whilethe camera 10 was moving on one direction on the path, and again whilethe camera was moving in an opposite direction on the same path. Thelandmark may be, for example, a tree in a lane divider.

In step 72, a time interval T is measured in the image sequence betweenthe two passings of the landmark. In step 74, the computer 28 uses theGPS data to compute a function for determining the time interval betweensuccessive passes of any point along the path. The function is then usedto find, for each point x on the path, a time of return Tr(x) whichmeasures the lapse of time between the two passings of each point. Instep 76, a point is identified for which Tr(x)=T. The identified pointprovides the GPS position of the landmark and hence, a GPS timeassociated with the landmark. Given the GPS time, a difference betweenthe GPS time and the video time associated with the landmark may becalculated for synchronizing any image frame acquired at a particularvideo time to the GPS position of the camera at a particular GPS time.

FIG. 5 is a flow diagram of an alternative embodiment for synchronizingthe image sequences with GPS position information. As in FIG. 4, theprocess illustrated in FIG. 5 also identifies, in step 80, a landmark inthe image sequence that appears in at least two distinct image frames.In step 82, a time phase is initialized to an arbitrary value using thecamera time stamp. In step 84, the computer 28 measures the distancetraveled between the two points on the path that correspond to the timeinstants in the image sequence where the landmark is seen from the twosides of the path. In step 86, an inquiry is made as to whether thedistance has been minimized. If the answer is NO, the time phase ismodified in step 88, and the process returns to step 84 where thedistance is measured again.

In another embodiment, the synchronization does not occur as apost-production process, but occurs in real-time as the image andposition sequences are acquired. FIG. 6 is a block diagram of a portionof the data acquisition and processing system of FIG. 1 allowing areal-time synchronization of image and position data. A UTC clockgenerator 90 provides to the data acquisition computer 34 the UTC timeassociated with each GPS position of the recording camera 10 as thecamera moves along the path. The video time produced by a camera clock92 is also provided to the data acquisition computer 34 via thecommunications port 24. A UTC card 94 on the computer 34 correlates thevideo time to the UTC time. Thus, the video image acquired at the videotime may be correlated to the GPS position of the camera during therecording of the image.

FIG. 7 is yet another embodiment for synchronizing the image sequenceswith the GPS position of the recording camera 10. In step 100, thepost-processing computer 28 computes the temporal variation in the imagevalues (i.e. optical flow) of the bottom pixel rows in the imagesequence. Thus, the average velocity of each of the pixels in the rowmay be obtained. In step 102, the tangential velocity of the camera 10is obtained from the GPS reading. The average velocity for the computedpixels is directly proportional to the vehicle tangential velocity.Thus, in step 104, the time phase between the position and videosequences may be determined as a time delay maximizing the alignment oflocal maxima and local minima between the average pixel velocity and thevehicle tangential velocity. This time phase is then read out in step106.

FIG. 8 is a more detailed flow diagram of step 64 of FIG. 3 forsegmenting the trajectory followed by one or more recording cameras 10and labeling the segments with an identifier. In the one camerascenario, the camera is moved along the path making a right turn at eachintersection until a block 112 has been filmed, as is illustrated inFIG. 9. The camera then moves to a second block 114 to film the objectson that block. Thus, a particular path 110 adjoining the two blocks 112,114 is traversed twice on opposite directions allowing the filming ofthe objects on each side of the path.

In step 120, the post-processing computer 28 segments the camera'strajectory into straight segments by detecting the points of maximumcurvature (i.e. where the turns occur). In this regard, the latitude andlongitude coordinates provided by the GPS receiver 16 are converted intotwo-dimensional Mercator coordinates according to well-known methods. Aspline interpolation is then obtained from the two-dimensional Mercatorcoordinates and the resulting spline function is parameterized inarc-length. The computer 28 obtains a new sampling of the coordinatesfrom the spline function by uniformly sampling the coordinates in anarc-length increment of about one meter while detecting the points inthe new sequence where a turn was made. The place where a turn occurs isassumed to be the place of an intersection of two segments.

Preferably, the computer 28 performs a singular value decompositioncomputation according to well-known methods to detect the turns. In thisregard, the computer selects an observation window containing N samplepoints that is moved along the spline for calculating an indexindicative of the overall direction (i.e. alignment) of the points inthe window. The higher the index, the less aligned the points, and themore likely that the camera was making a turn at those points. Thepoints are least aligned at the center of a turn, and thus, the computerselects as a turn coordinate a point in the observation window where theindex is at a local maximum. The computer 28 gathers all the pointswhose indexes correspond to local maxima and stores them into an arrayof turn coordinates.

In step 122, the computer 28 determines the center of an intersection bygrouping the turn coordinates into clusters where turns that belong tothe same cluster are turns made on the same intersection. An average ofthe turn coordinates belonging to the same cluster is then calculatedand assigned as the intersection coordinate.

The endpoints of each straight segment are identified based on thecalculated intersection coordinates. In this regard, an intersectioncoordinate at the start of the segment is identified and assigned to thesegment as a segment start point (the “From” intersection coordinate).An intersection coordinate at the end of the segment is also identifiedand assigned to the segment as a segment end point (the “To”intersection coordinate).

In the scenario where at least two side cameras are utilized, eachcamera films the objects on each side of the path during the first passon the path. Thus, unlike the single camera scenario where a turn ismade at each intersection to move the camera along the same path twicebut in opposite directions, a turn is not made at each intersection inthe two camera scenario. Therefore, instead of identifying the points ofmaximum curvature for determining the intersection coordinates, theintersection coordinates are simply detected by tracking the GPS dataand identifying where the segments orthogonally intersect.

The computer 28 associates the calculated segments with informationobtained from a geographic information database 128 and stores it into asegments table as is described in further detail below. In the scenariowhere composite images of a city are created, the geographic informationdatabase 128 includes a map of the city where the endpoints of eachstreet segment on the map are identified by latitude and longitudeinformation. The database 128 further includes a street name and numberrange for each street segment on the map. Such databases arecommercially available from third parties such as NavigationTechnologies and Etak, Inc.

In correlating the segments of the camera's trajectory with the segmentsin the geographic information database 128, the computer, in step 124,determines the correspondences between the “From” and “To” coordinatescalculated for the trajectory segment with intersection coordinates ofthe segments in the database. The computer 28 selects the segment in thegeographic information database 128 which endpoints are closest to thecomputed “From” and “To” coordinates, as the corresponding segment.

In step 126, the computer labels each trajectory segment withinformation that is associated with the corresponding segment in thedatabase 128. Thus, if each segment in the database 128 includes astreet name and number, this information is also associated with thetrajectory segment.

FIG. 10 is a more detailed flow diagram of step 66 of FIG. 3 forcreating a composite image of a segment of the camera's path accordingto one embodiment of the invention. In step 130, the computer 28computes the arc length coordinate Xc of the center of the segment whichis then set as the center of the composite image. In step 132, thecomputer identifies the optical rays 46 (FIG. 2) originating from thefictitious camera 44 by computing an array of equidistant positions X1,X2, . . . , Xn along the camera's trajectory, centered around Xc. Thenumber of computed positions preferably depend on the number of opticalcolumns that are to be created in the composite image.

In step 134, the computer 28 uses the position information obtained fromthe GPS receiver 16 and/or inertial navigation system 20 to map eachposition Xi on the trajectory to a position time Ti. Thus, if GPS datais used to determine the camera's position, each position Xi of thecamera 10 is mapped to a UTC time.

In step 136, the computer 28 uses the time phase information computed inthe synchronization step 62 of FIG. 3 to convert the position times tovideo times. For each identified video time, the computer 28, in step138, identifies an associated image frame and extracts a column of RGBpixel values from the frame corresponding to the optical rays 46originating from the fictitious camera 44. In step 140, the column ofRGB pixel values are stacked side by side to generate a single imagebitmap forming the composite image.

FIG. 11 is a more detailed flow diagram of step 138 for identifying andretrieving a column of RGB pixel values for a particular video time Tiaccording to one embodiment of the invention. In step 150, the computer28 identifies an image frame with frame index Fi acquired at time Ti.Because the image frames are acquired at a particular frame rate (e.g.one frame every {fraction (1/30)} seconds), there may be a particulartime Ti for which an image frame was not acquired. In this scenario, theframe closest to time Ti is identified according to one embodiment ofthe invention.

In step 152, the current position of the image sequence is set to theimage frame with index Fi, and the frame is placed into a frame buffer.In step 154, a column in the image frame with an index i is read outfrom the frame buffer.

FIG. 12 is a flow diagram of an alternative embodiment for identifyingand retrieving a column of RGB pixel values for a particular video timeTi. If an image frame was not acquired at exactly time Ti, the computer,in step 160, identifies 2*N image frames that are closest to time Ti,where N≧1. Thus, at least two image frames closest to time Ti areidentified. In step 162, the computer computes an optical flow field foreach of the 2*N image frames and in step 164, infers the column of RGBvalues for a column i at time Ti. In the situation where only two imageframes are used to compute the optical flow, the computer identifies foreach pixel in the first image frame a position X1 and a position timeT1. A corresponding pixel in the second frame is also identified alongwith a position X2 and a position time T2. The position X′ of each pixelat time Ti is then computed where X′=X1+((Ti−T1)/(T2−T1))*(X2−X1). Giventhe position of each pixel at time Ti, a new frame that corresponds totime Ti may be inferred. The computer 28 may then extract the column ofRGB values from the new frame for a column i.

Preferably, the computer 28 creates multiple composite images at uniformincrements (e.g. every 8 meters) along a segment. In the scenario wherethe composite images are created for street segments, the compositeimages depict the view of the objects on each side of the street. Thecomposite images are then stored in the image database 28 along withvarious tables that help organize and associate the composite imageswith street segment information.

According to one embodiment of the invention, the image database 32includes composite images of a geographic area which together provide avisual representation of at least the static objects in the entire area.Thus, if the geographic area is a particular city, the composite imagesdepict the city on a street-by-street basis, providing a visual image ofthe buildings, stores, apartments, parks, and other objects on thestreets. The system further includes an object information database withinformation about the objects being depicted in the composite images. Ifthe geographic area being depicted is a city, the object informationdatabase contains information about the structures and businesses oneach city street. In this scenario, each record in the objectinformation database is preferably indexed by a city address.

FIG. 13 is an illustration of an exemplary street segments table 170including the street segments in the camera's trajectory. The table 170suitably includes multiple entries where each entry is a record specificto a particular street segment. A particular street segment recordincludes an index identifying the street segment (segment ID) 172 aswell as the corresponding street name 174 obtained from the geographicinformation database 128 (FIG. 12). A particular street segment recordalso includes the direction of the street (North, South, East, or West)176 with respect to a main city street referred to as a city hub. Thedirection information generally appears in an address in front of thestreet name. A city, state, and/or country fields may also be added tothe table 170 depending on the extent of the geographic area covered inthe image database 32.

A street segment record includes the endpoint coordinates 178 of thecorresponding street segment in the geographic information database 128.An array of segment IDs corresponding to street segments adjacent to thesegment start point are identified and stored in field 180 along withthe direction in which they lie with respect to the start point (e.g.North, South, East, or West). Similarly, an array of segment IDscorresponding to street segments adjacent to the segment end point arealso identified and stored in field 182. These segments are also orderedalong the direction in which they lie.

In addition to the above, a street segment record includes a distance ofthe start of the trajectory segment from the city hub 184. The city hubgenerally marks the origin of the streets from which street numbers andstreet directions (North, South, East, or West) are determined. Streetnumbers are generally increased by two at uniform distances (e.g. every12.5 feet) starting from the hub. Thus the distance from the hub allowsa computation of the street numbers on the street segment. In a onecamera situation where each segment is traversed twice, the distancefrom the hub is computed for each camera trajectory. In a multiplecamera scenario, however, only one distance is computed since the cameratraverses the segment only once.

Also included in a street segment record is a length of the trajectorysegment. Such a length is computed for each trajectory in a one camera10 scenario because the movement of the camera 10 is not identicalduring the two traversals of the segment.

Each street segment record 170 further includes an offset value 188 foreach side of the street. The offset is used to correct the streetnumberings computed based on the distance information. Such acomputation may not be accurate if, for instance, there is an unusuallywide structure on the segment that is erroneously assigned multiplestreet numbers because it overlaps into the area of the next numberassignment. In this case, the offset is used to decrease the streetnumbers on the segment by the offset value.

FIG. 14 is an illustration of an exemplary image coordinates table 200for associating the composite images with the street segments in thestreet segments table 170. The image coordinates table 200 includes aplurality of composite image records where each record includes asegment ID 202 of the street segment being depicted in the compositeimage. In addition, each composite image record includes information ofthe side of the street segment 204 being depicted. For example, the sidemay be described as even or odd based on the street numbers on the sideof the street being depicted. Each composite image entry also includes adistance from the segment origin to the center Xc of the composite image206 indicating the position along the street segment for which the imagewas computed. The distance information is used to retrieve anappropriate composite image for each position on the street segment.

FIG. 15 is an illustration of an exemplary segment block table 210 forallowing an efficient determination of a segment ID that is closest to aparticular geographic coordinate. In this regard, the geographic areadepicted in the image database 32 is preferably partitioned into a gridof square blocks where each block includes a certain number of streetsegments. The blocks are assigned block labels preferably correspondingto the center longitude and latitude coordinates of the block. The blocklabels are stored in a block label field 212. Associated with each blocklabel are segment IDs 214 corresponding to the street segments in theblock. Given the coordinates of a particular geographic location, theblock closest to the given coordinates may be identified to limit thesearch of street segments to only street segments within the block.

In a particular use of the system, a user places inquiries about alocation in a geographic area depicted in the image database 32. Forexample, the user may enter an address of the location, enter thegeographic coordinates of the location, select the location on a map ofthe geographic area, or specify a displacement from a current location.Preferably, the user has access to a remote terminal that communicateswith a host computer to service the user requests. The host computerincludes a processor programmed with instructions to access the imagedatabase 32 in response to a user request and retrieve composite imagesabout the particular location. The processor is also programmed withinstructions to access the geographic and object information databasesto retrieve maps and information on the businesses in the geographicarea. The retrieved data is then transmitted to the requesting remoteuser terminal for display thereon.

The remote user terminals may include personal computers, set-top boxes,portable communication devices such as personal digital assistants, andthe like. The visual component of each remote user terminal preferablyincludes a VGA or SVGA liquid-crystal-display (LC) screen, an LEDdisplay screen, or any other suitable display apparatus. Pressuresensitive (touch screen) technology may be incorporated into the displayscreen so that the user may interact with the remote user terminal bymerely touching certain portions of the screen. Alternatively, akeyboard, keypad, joystick, mouse, and/or remote control unit isprovided to define the user terminal's input apparatus.

Each remote user terminal includes a network interface for communicatingwith the host computer via wired or wireless media. Preferably, thecommunication between the remote user terminals and the host computeroccurs over a wide area network such as the Internet.

In an alternative embodiment of the invention, the image, geographicinformation, and object information databases reside locally at the userterminals in a CD, DVD, hard disk drive, or any other type of massstorage media. In this embodiment, the user terminals include aprocessor programmed with instructions to receive queries from the userabout a particular geographic location and retrieve composite images andassociated information in response to the user queries.

FIG. 16 is an illustration of an exemplary graphical user interface(GUI) for allowing the user to place requests and receive informationabout particular geographic locations. The GUI includes address inputfields 220 allowing the user to enter the street number, street name,city and state of the particular location he or she desires to view.Actuation of a “See It” button 222 causes the user terminal to transmitthe address to the host computer to search the image and geographiclocation databases 32, 128 for the composite image and map correspondingto the address. Furthermore, the host computer searches the objectinformation database to retrieve information about the objects depictedin the composite image.

The retrieved composite image and map are respectively displayed on thedisplay screen of the requesting user terminal in a map area 226 and animage area 224. The map is preferably centered around the requestedaddress and includes a current location cursor 228 placed on a positioncorresponding to the address. The current location identifier 228 may,for instance, take the shape of an automobile.

The composite image displayed on the image area 224 provides a view of aside of the street (even or odd) based on the entered street number. Theuser may obtain information about the objects being visualized in thecomposite image by actuating one of the information icons 234 above theimage of a particular object. In displaying the information icons 234, arange of street addresses for the currently displayed image is computed.The listings in the object information database with street numbers thatfall inside the computed range are then selected and associated with theinformation icons 234 displayed on top of the image of the object.

If the objects are business establishments, the information displayedupon actuating the information icons 234 may include the name, address,and phone number 236 of the establishment. This information ispreferably displayed each time the user terminal's cursor or pointingdevice is passed above the icon. In addition, if the establishment isassociated with a particular Web page, the information icon 234functions as a hyperlink for retrieving and displaying the Web page,preferably on a separate browser window.

The user may obtain a close-up view of a particular object in thecomposite image by selecting the object in the image. A close-up view ofthe object is then obtained by computing the distance of the selectedobject from the origin of the street segment where they object lies. Thelocation on the segment of the closest close-up image is computed andretrieved from the image database 32. The close-up image is thenprovided in the image area 224 or in a separate browser window.

A “Switch View” button 230 allows the user to update the currentcomposite image providing a view of one side of the street with acomposite image of the other side of the street. In a multiple camerascenario, each actuation of the “Switch View” button 230 provides adifferent view of the street. The current view is preferably identifiedby a direction identifier (not shown) on or close to the currentlocation identifier 228. For instance, one side of the current locationidentifier 228 may be marked with a dot or an “X” to identify the sideof the street being viewed. Alternatively, an arrow may be placed nearthe current location identifier 228 to identify the current viewingdirection.

The composite image is also updated as the user navigates through thestreets using the navigation buttons 232. From a current location, theuser may choose to navigate north, south, west, and east by actuatingthe corresponding buttons. Preferably, only the navigation buttonscorresponding to the possible direction of motions from the currentposition are enabled. As the user actuates one of the buttons, thecurrent position is incremented by a predetermined amount, currently setto eight meters, to the next available composite image on the current oradjacent segment. The image area 224 is then updated with the newcomposite image.

FIG. 17 is a flow diagram of the process executed by the host computerfor obtaining image and location information of an express streetaddress entered in the address input fields 220. A similar process isexecuted by the user terminal in the embodiment where the location andimage information are stored locally at the user terminal.

The process starts, and in step 240, the user requests information abouta particular street address by entering the address in the address inputfields 220. In step 242, the address is transmitted to the host computerpreferably over a wide area network such as the Internet. In step 244, aquery is run on the host computer to locate the street segment index inthe street segment table 170 (FIG. 13) corresponding to the requestedaddress. In this regard, the computer searches the street segment table170 for street segments that match the desired street name 174 as wellas a city, state, or country if applicable. For each street segmentmatching the street name, the computer computes the starting streetnumber on that segment preferably based on the following formula:Start Number=(round((Distance from Hub+Offset)/K)*2)The distance from the hub 184 and offset 188 values are obtained fromthe street segment table 170. The value K is the distance assumedbetween any two street numbers on the segment.

The ending street number on the street segment is also calculated usinga similar formula:End Number=(round((Distance from Hub+Offset+length)/K)*2)The length is the length 186 value obtained from the street segmenttable 170.

Once the start and end street numbers are calculated for a particularstreet segment, the computer determines whether the requested streetnumber lies within the start and end street numbers. If it does, thecomputer returns the corresponding segment ID 172. Furthermore, thecomputer determines the distance of the requested street number from thestart of the street segment for determining the position of the streetnumber on the street segment.

In step 246, the host computer transmits the query result to therequesting user terminal along with a map of the input locationretrieved from the geographic information database 128. In step 248, therequesting user terminal downloads from the host computer a record fromthe street segments table 170 corresponding to the identified streetsegment. Furthermore, the user terminal also retrieves the computedstart and end street numbers of the street segment, a list of computedcomposite images for both sides of the street segment in the imagecoordinates table 200 (FIG. 14), and information of the objects visibleon the street segment in the object information database.

In step 250, the user terminal downloads a composite image for theappropriate side of the street from the host computer that has adistance from the origin of the street segment to the center of thecomposite image 206 (FIG. 14) that is closest to the distance of thedesired street number from the origin. The display on the user terminalis then updated in step 252 with the new location and image information.

FIG. 18 is a flow diagram of the process executed by the host computerfor obtaining image and location information of a particular locationselected on the map displayed in the map area 226. A similar process isexecuted by the user terminal in the embodiment where the location andimage information are stored locally at the user terminal.

The process starts, and in step 260, the user requests information abouta particular street address by selecting a location on the map. In step262, the map coordinates are converted from screen coordinates togeographic location coordinates (x,y) and transmitted to the hostcomputer preferably over the Internet. In step 244, a query is run onthe host computer to locate the street segment index in the streetsegment table 170 (FIG. 13) corresponding to the geographic locationcoordinates. In this regard, the computer searches the segment blocktable 210 (FIG. 15) for a block that includes the street segmentcorresponding to the input location. In order to locate such a block,the computer rounds the identified geographic location coordinates basedpreferably on the size of the block. The rounded (x,y) coordinates maythus be represented by ((round (x/B))*B, (round y/B)*B)), where B is thelength of one of the block sides. The computer then compares the roundednumber to the coordinates stored in the block label field 212 andselects the block with the label field 212 equal to the roundedcoordinate. Once the appropriate block is identified, the computerproceeds to retrieve the segment IDs 214 associated with the block. Thegeographic coordinates of the desired location are then compared withthe endpoint coordinates of each street segment in the block forselecting the closest street segment.

In step 266, the segment ID of the closest street segment is returned tothe user terminal. Additionally, a new map of the desired location maybe transmitted if the previous map was not centered on the desiredlocation.

In step 268, the requesting user terminal downloads from the hostcomputer a street segment record in the street segments table 170corresponding to the identified street segment. The user terminal alsoretrieves the calculated start and end street numbers of the streetsegment, a list of computed composite images for both sides of thestreet the segment in the image coordinates table 200 (FIG. 14), andinformation of the objects visible on the street segment in the objectinformation database.

In step 270, the user terminal downloads the composite imagecorresponding to the geographic coordinates of the input location. Toachieve this, the geographic coordinates are converted to a distancealong the identified street segment. The user terminal downloads acomposite image that has a distance from the origin of the streetsegment to the center of the composite image 206 (FIG. 14) that isclosest to the distance of the input location from the origin. Thedisplay on the user terminal is then updated in step 272 with the newlocation and image information.

Although this invention has been described in certain specificembodiments, those skilled in the art will have no difficulty devisingvariations which in no way depart from the scope and spirit of thepresent invention. For example, the composite images may be made intostreaming video by computing the composite images at small incrementsalong the path (e.g. every 30 cm). Furthermore, the composite images maybe computed at several resolutions by moving the fictitious camera 44(FIG. 2) closer or further away from the path to decrease or increaseits field of view and provide the user with different zoom levels of theimage.

Variation may also be made to correct any distortions in the perspectiveof the composite image along the vertical y-axis direction. Theextraction of the optical columns from the acquired image frames mayintroduce such a distortion since the sampling technique used along thehorizontal x-axis direction is not applied along the y-axis. Such adistortion may be corrected by estimating the depth of each pixel in thecomposite image using optical flow. The aspect ratio of each pixel maybe adjusted based on the distance of the object visualized in the pixel.The distortion may also be corrected by acquiring images from an arrayof two or more video cameras 10 arranged along the vertical y-axis inaddition to the cameras in the horizontal axis.

The described method of generating composite images also relies on anassumption that the camera's trajectory is along a straight line. Ifthis is not the case and the vehicle carrying the camera makes a lanechange, makes a turn, or passes over a bump, the choice of the opticalcolumn extracted from a particular image frame may be incorrect. Thedistortion due to such deviations from a straight trajectory may,however, be corrected to some degree using optical flow to detect suchsituations and compensate for their effect.

It is therefore to be understood that this invention may be practicedotherwise than is specifically described. Thus, the present embodimentsof the invention should be considered in all respects as illustrativeand not restrictive, the scope of the invention to be indicated by theappended claims and their equivalents rather than the foregoingdescription.

1. A method for creating a composite image of at least one object, themethod comprising: recording a plurality of images of the objects usingan image recording device moving along a path; obtaining positioninformation of the image recording device as the image recording devicemoves along the path; associating the position information with theplurality of images; and processing image data acquired from theplurality of images to create a composite image representing the object,wherein the composite image simulates a view of the object from aparticular location that is situated off of the path of the imagerecording device.
 2. The method of claim 1, wherein the obtaining ofposition information comprises obtaining Global Positioning System (GPS)data.
 3. The method of claim 1, wherein the obtaining of positioninformation comprises: obtaining acceleration information of the imagerecording device as the image recording device moves along the path; andderiving the position information from the acceleration information. 4.The method of claim 1, wherein the obtaining of position informationcomprises deriving the position information of the image recordingdevice at a particular time by computing a motion of objects in aplurality of images closest to the particular time.
 5. The method ofclaim 1, wherein the associating of the position information comprisescorrelating times associated with the position information to times ofacquisition of the plurality of images.
 6. The method of claim 1,wherein the processing of the image data comprises: identifying aplurality of optical rays originating from the particular location;selecting for each optical ray an image including a correspondingoptical ray originating from a position on the path; extracting imagedata for the corresponding optical ray from the selected images; andcombining the extracted image data to form the composite image.
 7. Themethod of claim 6, wherein the selecting of an image for each opticalray comprises: determining the particular position on the path where theimage recording device would have been located for recording an imageincluding the corresponding optical ray; calculating a time associatedwith the determined position; and identifying an image recorded at thecalculated time.
 8. The method of claim 6, wherein the selecting of animage for each optical ray comprises: determining the particularposition on the path where the image recording device would have beenlocated for recording an image including the corresponding optical ray;calculating a time associated with the determined position; selecting animage recorded closest to the calculated time.
 9. The method of claim 6,wherein the selecting of an image for each optical ray comprises:determining the particular position on the path where the imagerecording device would have been located for recording an imageincluding the corresponding optical ray; calculating a time associatedwith the determined position; selecting a plurality of images recordedclosest to the calculated time; computing a motion of objects in theselected images; and creating a new image frame for the calculated timebased on the computed motion of objects.
 10. The method of claim 1,wherein the image data comprises a set of pixel values.
 11. The methodof claim 1, wherein the recording of the images comprises recording theimages from multiple viewing directions using multiple image recordingdevices.
 12. A method for creating a composite image database of aparticular geographic area, the method comprising: recording a pluralityof images of a series of objects using an image recording device movingalong a path; obtaining position information of the image recordingdevice as the image recording device moves along the path; associatingthe position information with the plurality of images; processing imagedata acquired from the plurality of images to create a composite imagedepicting a view of the series of objects from a particular location;partitioning the path into a plurality of discrete segments; associatingthe composite image to one of the discrete segments; and storing thecomposite image and association information in the composite imagedatabase.
 13. The method of claim 12, wherein the recording of theimages comprises recording the images from multiple viewing directionsusing multiple image recording devices.
 14. The method of claim 12,wherein the obtaining of position information comprises obtaining GlobalPositioning System (GPS) data.
 15. The method of claim 12, wherein theobtaining of position information comprises: obtaining accelerationinformation of the image recording device as the image recording devicemoves along the path; and deriving the position information from theacceleration information.
 16. The method of claim 12, wherein theobtaining of position information comprises deriving the positioninformation of the image recording device at a particular time bycomputing a motion of objects in a plurality of images closest to theparticular time.
 17. The method of claim 12, wherein the associating ofthe position information comprises correlating times associated with theposition information to times of acquisition of the plurality of images.18. The method of claim 12, wherein the object is located on a firstside of the path and the composite image simulates a view of the objectfrom the particular location on a second side of the path opposite fromthe first side.
 19. The method of claim 12, wherein the processing ofthe image data comprises: identifying a plurality of optical raysoriginating from the particular location; selecting for each optical rayan image including a corresponding optical ray originating from aposition on the path; extracting image data for the correspondingoptical ray from the selected images; and combining the extracted imagedata to form the composite image.
 20. The method of claim 19, whereinthe selecting of an image for each optical ray comprises: determiningthe particular position on the path where the image recording devicewould have been located for recording an image including thecorresponding optical ray; calculating a time associated with thedetermined position; and identifying an image recorded at the calculatedtime.
 21. The method of claim 19, wherein the selecting of an image foreach optical ray comprises: determining the particular position on thepath where the image recording device would have been located forrecording an image including the corresponding optical ray; calculatinga time associated with the determined position; and selecting an imagerecorded closest to the calculated time.
 22. The method of claim 19,wherein the selecting of an image for each optical ray comprises:determining the particular position on the path where the imagerecording device would have been located for recording an imageincluding the corresponding optical ray; calculating a time associatedwith the determined position; selecting a plurality of images recordedclosest to the calculated time; calculating a motion of objects in theselected images; and creating a new image frame for the calculated timebased on the computed motion of objects.
 23. The method of claim 12,wherein the image data comprises a set of pixel values.
 24. The methodof claim 12, wherein the partitioning of the path into a plurality ofdiscrete segments comprises: detecting an intersection on the path; andidentifying the position of the intersection.
 25. The method of claim 24wherein the detecting of the intersection comprises detecting a point ofmaximum curvature on the path.
 26. The method of claim 12 wherein eachdiscrete segment is associated with a plurality of composite images,each composite image depicting a portion of the associated segment. 27.The method of claim 12, wherein each discrete segment is a portion of astreet and the method further comprises associating each discretesegment with a street name and number range.
 28. A system for creating acomposite image of a series of objects, the system comprising: an imagerecording device moving along a path and recording a plurality of imagesof the objects; a means for receiving position information of the imagerecording device as the image recording device moves along the path; anda processor receiving the plurality of images and position information,the processor being operable to execute program instructions including:associating the position information with the plurality of images; andprocessing image data acquired from the plurality of images to create acomposite image representing the object, wherein the composite imagesimulates a view of the object from a particular location that issituated off of the path of the image recording device.
 29. The systemof claim 28 wherein multiple image recording devices record the imagesfrom multiple viewing directions.
 30. The system of claim 28, whereinthe means for receiving position information comprises means forobtaining acceleration information of the image recording device as theimage recording device moves along the path.
 31. The system of claim 28,wherein the means for receiving position information comprises means forreceiving GPS data.
 32. The system of claim 28, wherein the associatingof the position information comprises correlating times associated withthe position information to times of acquisition of the plurality ofimages.
 33. The system of claim 28, wherein the processing of the imagedata comprises: identifying a plurality of optical rays originating fromthe particular location; selecting for each optical ray an imageincluding a corresponding optical ray originating from a position on thepath; extracting image data for the corresponding optical ray from theselected images; and combining the extracted image data to form thecomposite image.
 34. The system of claim 33, wherein the selecting of animage for each optical ray comprises: determining the particularposition on the path where the image recording device would have beenlocated for recording an image including the corresponding optical ray;calculating a time associated with the determined position; andidentifying an image recorded at the calculated time.
 35. The system ofclaim 33, wherein the selecting of an image for each optical raycomprises: determining the particular position on the path where theimage recording device would have been located for recording an imageincluding the corresponding optical ray; calculating a time associatedwith the determined position; selecting an image recorded closest to thecalculated time.
 36. The system of claim 33, wherein the selecting of animage for each optical ray comprises: determining the particularposition on the path where the image recording device would have beenlocated for recording an image including the corresponding optical ray;calculating a time associated with the determined position; selecting aplurality of images recorded closest to the calculated time; calculatinga motion of objects in the selected images; and creating a new imageframe for the calculated time based on the computed motion of objects.37. The system of claim 28, wherein the image data comprises a set ofpixel values.
 38. A system for creating a composite image database of aparticular geographic area, the system comprising: an image recordingdevice moving along a path and recording a plurality of images of aseries of objects; means for obtaining position information of the imagerecording device as the image recording device moves along the path;means for associating the position information with the plurality ofimages; means for processing image data acquired from the plurality ofimages to create a composite image depicting a view of the series ofobjects from a particular location; means for partitioning the path intoa plurality of discrete segments; means for associating the compositeimage to one of the discrete segments; and means for storing thecomposite image and association information in the composite imagedatabase.
 39. The system of claim 38 wherein multiple image recordingdevices record the images from multiple viewing directions.
 40. Thesystem of claim 38, wherein the means for associating comprises meansfor correlating times associated with the position information to timesof acquisition of the plurality of images.
 41. The system of claim 38,wherein the object is located on a first side of the path and thecomposite image simulates a view of the object from the particularlocation on a second side of the path opposite from the first side. 42.The system of claim 38, wherein the means for processing the image datacomprises: means for identifying a plurality of optical rays originatingfrom the particular location; means for selecting for each optical rayan image including a corresponding optical ray originating from aposition on the path; means for extracting image data for thecorresponding optical ray from the selected images; and means forcombining the extracted image data to form the composite image.
 43. Thesystem of claim 42, wherein the means for selecting an image for eachoptical ray comprises: means for determining the particular position onthe path where the image recording device would have been located forrecording an image including the corresponding optical ray; means forcalculating a time associated with the determined position; and meansfor identifying an image recorded at the calculated time.
 44. The systemof claim 42, wherein the means for selecting an image for each opticalray comprises: means for determining the particular position on the pathwhere the image recording device would have been located for recordingan image including the corresponding optical ray; means for calculatinga time associated with the determined position; and means for selectingan image recorded closest to the calculated time.
 45. The system ofclaim 42, wherein the means for selecting of an image for each opticalray comprises: means for determining the particular position on the pathwhere the image recording device would have been located for recordingan image including the corresponding optical ray; means for calculatinga time associated with the determined position; means for selecting aplurality of images recorded closest to the calculated time; means forcalculating a motion of objects in the selected images; and means forcreating a new image frame for the calculated time based on the computedmotion of objects.
 46. The system of claim 38, wherein the image datacomprises a set of pixel values.
 47. The system of claim 38, wherein themeans for partitioning the path comprises: means for detecting anintersection on the path; and means for identifying the position of theintersection.
 48. The system of claim 38 wherein each discrete segmentis associated with a plurality of composite images, each composite imagedepicting a portion of the associated segment.
 49. The system of claim38, wherein each discrete segment is a portion of a street and thesystem further comprises means for associating each discrete segmentwith a street name and number range.
 50. A computer-readable mediumcomprising: a program code embodied in the computer readable medium forcreating a composite image of a series of objects from a plurality ofimages acquired by an image recording device moving along a path, thecomputer-readable program segment comprising instructions for performingthe steps of: identifying a plurality of optical rays originating from aparticular location; selecting for each optical ray an image including acorresponding optical ray originating from a position on the path;extracting image data for the corresponding optical ray from theselected images; and combining the extracted image data to form thecomposite image.
 51. The computer-readable medium of claim 50, whereinthe step of selecting an image for each optical ray comprises:determining the particular position on the path where the imagerecording device would have been located for recording an imageincluding the corresponding optical ray; calculating a time associatedwith the determined position; and identifying an image recorded at thecalculated time.
 52. The computer-readable medium of claim 50, whereinthe step of selecting an image for each optical ray comprises:determining the particular position on the path where the imagerecording device would have been located for recording an imageincluding the corresponding optical ray; calculating a time associatedwith the determined position; selecting an image recorded closest to thecalculated time.
 53. The computer-readable medium of claim 50, whereinthe step of selecting an image for each optical ray comprises:determining the particular position on the path where the imagerecording device would have been located for recording an imageincluding the corresponding optical ray; calculating a time associatedwith the determined position; selecting a plurality of images recordedclosest to the calculated time; calculating a motion of objects in theselected images; and creating a new image frame for the calculated timebased on the computed motion of objects.
 54. The computer-readablemedium of claim 50, wherein the image data comprises a set of pixelvalues.